An Intelligent Image Classification Approach for Food Items Nutrition Facts

Abstract

Nutrition is essential for health and wellbeing. The state of health is determined by what one eats. Knowing the nutrient contents of food create awareness of what to eat and how much to eat. People are growing fond of the modern lifestyle and they merely eat to fill up their stomach. The UN report states that over 25 percent of the world’s population lack nutritious food. Lack of balanced diet may lead to obesity and other health related issues. Study further reveals that through appropriate diet and daily food consumption tracking, even obese people showed remarkable reduction in weight. Inspired by these findings in literature, a mobile application has been proposed to identify and classify Indian breakfast food items using a derivative of the Convolution Neural Network model called MobileNet. The identified images are further classified to determine the nutritive content in the food identified. In addition, the mobile App also summarizes the daily nutritional value of food consumed against the recommended nutritional value based on gender. Thus, the proposed work can be extended to monitor the daily food habits of people with health conscious and related issues.